A GPU approach to FDTD for Radio Coverage Prediction

摘要：

The bene.ts of using Finite-Difference alike methods for coverage prediction comprise highly accurate electromagnetic simulations that serve as a reliable input for wireless networks planning and optimization algorithms. These algorithms usually require several thousands of iterations in order to find the optimal network configuration, so to obtain results within reasonable computation times, the applied propagation models must be as fast as possible. In this study an implementation-oriented analysis on the suitability of using Graphics Processing Units (GPU) to perform Finite-Difference Time-Domain simulations is carried out. We believe that the recently released Compute Unified Device Architecture (CUDA) technology has opened the door for computational intensive algorithms such as FDTD to be considered for the first time as a precise and fast propagation model to predict radio coverage.

作者: Alvaro Valcarce Guillaume De La Roche Jie Zhang

作者单位: Centre for Wireless Network Design (CWiND)University of Bedfordshire,Luton,Bedfordshire,UK Centre for Wireless Network Design (CWiND) University of Bedfordshire,Luton,Bedfordshire,UK

会议类型: 国际会议

会议名称: The 11th IEEE International Conference on Communications Systems(第11届电子和电气工程师协会国际通信系统会议)(IEEE ICCS 2008)

会议地点: 广州

会议语种:英文

在线出版日期: 2008-11-19（万方平台首次上网日期，不代表论文的发表时间）